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The econometrics of financial markets

TL;DR: In this paper, Campbell, Lo, and MacKinlay present an attempt by three well-known and well-respected scholars to fill an acknowledged void in the empirical finance literature, a text covering the burgeoning field of empirical finance.
Abstract: This book is an ambitious effort by three well-known and well-respected scholars to fill an acknowledged void in the literature—a text covering the burgeoning field of empirical finance. As the authors note in the preface, there are several excellent books covering financial theory at a level suitable for a Ph.D. class or as a reference for academics and practitioners, but there is little or nothing similar that covers econometric methods and applications. Perhaps the closest existing text is the recent addition to the Wiley Series in Financial and Quantitative Analysis. written by Cuthbertson (1996). The major difference between the books is that Cuthbertson focuses exclusively on asset pricing in the stock, bond, and foreign exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM) consider empirical applications throughout the field of finance, including corporate finance, derivatives markets, and market microstructure. The level of anticipation preceding publication can be partly measured by the fact that at least three reviews (including this one) have appeared since the book arrived. Moreover, in their reviews, both Harvey (1998) and Tiso (1998) comment on the need for such a text, a sentiment that has been echoed by numerous finance academics.

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Citations
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TL;DR: In this article, the authors provide a model that links an asset's market liquidity and traders' funding liquidity, i.e., the ease with which they can obtain funding, to explain the empirically documented features that market liquidity can suddenly dry up, has commonality across securities, is related to volatility, is subject to flight to quality, and comoves with the market.
Abstract: We provide a model that links an asset's market liquidity - i.e., the ease with which it is traded - and traders' funding liquidity - i.e., the ease with which they can obtain funding. Traders provide market liquidity, and their ability to do so depends on their availability of funding. Conversely, traders' funding, i.e., their capital and the margins they are charged, depend on the assets' market liquidity. We show that, under certain conditions, margins are destabilizing and market liquidity and funding liquidity are mutually reinforcing, leading to liquidity spirals. The model explains the empirically documented features that market liquidity (i) can suddenly dry up, (ii) has commonality across securities, (iii) is related to volatility, (iv) is subject to “flight to quality¶, and (v) comoves with the market, and it provides new testable predictions. Keywords: Liquidity Risk Management, Liquidity, Liquidation, Systemic Risk, Leverage, Margins, Haircuts, Value-at-Risk, Counterparty Credit Risk

3,638 citations


Cites background from "The econometrics of financial marke..."

  • ...Empirically, fundamental volatility can be captured using price changes over a longer time period, and the total fundamental and liquidity-based volatility is captured by short-term price changes as in the literature on variance ratios (see e.g. Campbell, Lo, and MacKinlay (1997) )....

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Journal ArticleDOI
TL;DR: In this article, the authors provide a model that links a security's market liquidity and traders' funding liquidity, i.e., their availability of funds, to explain the empirically documented features that market liquidity can suddenly dry up (i) is fragile), (ii) has commonality across securities, (iii) is related to volatility, and (iv) experiences “flight to liquidity” events.
Abstract: We provide a model that links a security’s market liquidity — i.e., the ease of trading it — and traders’ funding liquidity — i.e., their availability of funds. Traders provide market liquidity and their ability to do so depends on their funding, that is, their capital and the margins charged by their financiers. In times of crisis, reductions in market liquidity and funding liquidity are mutually reinforcing, leading to a liquidity spiral. The model explains the empirically documented features that market liquidity (i) can suddenly dry up (i.e. is fragile), (ii) has commonality across securities, (iii) is related to volatility, (iv) experiences “flight to liquidity” events, and (v) comoves with the market. Finally, the model shows how the Fed can improve current market liquidity by committing to improve funding in a potential future crisis.

3,166 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the economic effects of conflict, using the terrorist conflict in the Basque Country as a case study, and found that after the outbreak of terrorism in the late 1960's, per capita GDP in the basque country declined about 10 percentage points relative to a synthetic control region without terrorism.
Abstract: This article investigates the economic effects of conflict, using the terrorist conflict in the Basque Country as a case study. We find that, after the outbreak of terrorism in the late 1960's, per capita GDP in the Basque Country declined about 10 percentage points relative to a synthetic control region without terrorism. In addition, we use the 1998-1999 truce as a natural experiment. We find that stocks of firms with a significant part of their business in the Basque Country showed a positive relative performance when truce became credible, and a negative relative performance at the end of the cease-fire.

3,128 citations

Journal ArticleDOI
Rama Cont1
TL;DR: In this paper, the authors present a set of stylized empirical facts emerging from the statistical analysis of price variations in various types of financial markets, including distributional properties, tail properties and extreme fluctuations, pathwise regularity, linear and nonlinear dependence of returns in time and across stocks.
Abstract: We present a set of stylized empirical facts emerging from the statistical analysis of price variations in various types of financial markets. We first discuss some general issues common to all statistical studies of financial time series. Various statistical properties of asset returns are then described: distributional properties, tail properties and extreme fluctuations, pathwise regularity, linear and nonlinear dependence of returns in time and across stocks. Our description emphasizes properties common to a wide variety of markets and instruments. We then show how these statistical properties invalidate many of the common statistical approaches used to study financial data sets and examine some of the statistical problems encountered in each case.

2,994 citations

References
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TL;DR: In this article, a stochastic model of nonsynchronous asset prices based on sampling with random censoring is developed to estimate the effects of infrequent trading on the time series properties of asset returns.
Abstract: We develop a stochastic model of nonsynchronous asset prices based on sampling with random censoring In addition to generalizing existing models of non-trading our framework allows the explicit calculation of the effects of infrequent trading on the time series properties of asset returns These are empirically testable implications for the variances, autocorrelations, and cross-autocorrelations of returns to individual stocks as well as to portfolios We construct estimators to quantify the magnitude of non-trading effects in commonly used stock returns data bases and show the extent to which this phenomenon is responsible for the recent rejections of the random walk hypothesis

695 citations

Book
16 Sep 2011
TL;DR: In this paper, a stochastic model of nonsynchronous asset prices based on sampling with random censoring is developed, which allows the explicit calculation of the effects of infrequent trading on the time series properties of asset returns.
Abstract: We develop a stochastic model of nonsynchronous asset prices based on sampling with random censoring. In addition to generalizing existing models of nontrading, our framework allows the explicit calculation of the effects of infrequent trading on the time series properties of asset returns. These are empirically testable implications for the variances, autocorrelations, and cross-autocorrelations of returns to individual stocks as well as to portfolios. We construct estimators to quantify the magnitude of nontrading effects in commonly used stock returns data bases, and show the extent to which this phenomenon is responsible for the recent rejections of the random walk hypothesis.

575 citations

Journal ArticleDOI
TL;DR: In this paper, the authors estimate the conditional distribution of trade-to-trade price changes using ordered probit, a statistical model for discrete random variables, recognizing that transaction price changes occur in discrete increments, typically eighths of a dollar, and occur at irregularly-spaced time intervals.

514 citations

Book
01 Jan 2004
TL;DR: This new edition of the hugely successful Quantitative Financial Economics has been revised and updated to reflect the most recent theoretical and econometric/empirical advances in the financial markets as discussed by the authors.
Abstract: This new edition of the hugely successful Quantitative Financial Economics has been revised and updated to reflect the most recent theoretical and econometric/empirical advances in the financial markets. It provides an introduction to models of economic behaviour in financial markets, focusing on discrete time series analysis. Emphasis is placed on theory, testing and explaining ‘real-world’ issues. The new edition will include: Updated charts and cases studies. New companion website allowing students to put theory into practice and to test their knowledge through questions and answers. Chapters on Monte Carlo simulation, bootstrapping and market microstructure.

272 citations

Posted Content
TL;DR: In this article, the authors propose a class of continuous-time linear diffusion processes for asset prices that can capture a wider variety of predictability, and provide several numerical examples that illustrate their importance for pricing options and other derivative assets.
Abstract: Option pricing formulas obtained from continuous-time no- arbitrage arguments such as the Black-Scholes formula generally do not depend on the drift term of the underlying asset's diffusion equation. However, the drift is essential for properly implementing such formulas empirically, since the numerical values of the parameters that do appear in the option pricing formula can depend intimately on the drift. In particular, if the underlying asset's returns are predictable, this will influence the theoretical value and the empirical estimate of the diffusion coefficient a. We develop an adjustment to the Black-Scholes formula that accounts for predictability and show that this adjustment can be important even for small levels of predictability, especially for longer-maturity options. We propose a class of continuous-time linear diffusion processes for asset prices that can capture a wider variety of predictability, and provide several numerical examples that illustrate their importance for pricing options and other derivative assets.

217 citations


"The econometrics of financial marke..." refers background in this paper

  • ...For example, much of the chapter on market microstructure revolves around Lo and MacKinlay (1990) and Hausman et al....

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  • ...For example, much of the chapter on market microstructure revolves around Lo and MacKinlay (1990) and Hausman et al. (1992). I don’t question the contribution of these papers, but there is a wealth of other empirical literature that is slighted by omission. Similarly, is Lo and Wang (1995) the most important paper in the area of derivative pricing? Judging by the space allocation in Chapter 9, the authors appear to think so....

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  • ...For example, much of the chapter on market microstructure revolves around Lo and MacKinlay (1990) and Hausman et al. (1992). I don’t question the contribution of these papers, but there is a wealth of other empirical literature that is slighted by omission....

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  • ...The major difference between the books is that Cuthbertson focuses exclusively on asset pricing in the stock, bond, and foreign exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM) consider empirical applications throughout the field of finance, including corporate finance, derivatives markets, and market microstructure....

    [...]

  • ...The major difference between the books is that Cuthbertson focuses exclusively on asset pricing in the stock, bond, and foreign exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM) consider empirical applications throughout the field of finance, including corporate finance, derivatives markets, and market microstructure. The level of anticipation preceding publication can be partly measured by the fact that at least three reviews (including this one) have appeared since the book arrived. Moreover, in their reviews, both Harvey (1998) and Tiso (1998) comment on the need for such a text, a sentiment that has been echoed by numerous finance academics....

    [...]